Code confidence for the agentic software factory

Code is abundant.Confidence is scarce.

Sonar provides independent, zero-trust verification and governance so you can confidently ship every change, at any volume, at agent speed.

The code confidence formula
Code confidence =
01 / 04 · Intent

Intent: goals and standards, clearly specified

Confidence gap to close

Agents often lack the context to work well in large, complex codebases. Without clear goals and standards, they guess.

How Sonar helps

Sonar Vortex gives agents codebase context and constraints before they write, so the change fits your design on the first attempt.

02 / 04 · Guiderails

Guiderails: that guide and govern

Confidence gap to close

Agents need constraints that hold as they write, not after. Without them, large codebases drift and LLM judges are left to decide what is acceptable.

How Sonar helps

Sonar Vortex delivers your architecture, coding standards, security policy and approved libraries to the agent before it writes a line.

03 / 04 · Verification

Verification: thorough, independent, fixed

Confidence gap to close

Even the best models make mistakes, and errors compound on longer tasks. LLM reviewers are inconsistent, and attackers are moving faster.

How Sonar helps

SonarQube applies the same quality profiles across every agent and model, with Gitar for agentic review and Hunter Agent and Remediation Agent in the background.

04 / 04 · Evidence

Evidence: consistent, auditable, repeatable

Confidence gap to close

People tend to trust AI output even when it is wrong. Without a consistent record of every check, there is nothing to defend to an auditor.

How Sonar helps

SonarQube quality gates, with an auditable record of every check. Time stamped, traceable, tied to the commit, defensible.

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Everything you need to verify AI code

SonarQube image

SonarQube

Code verification and governance

SonarQube Advanced Security image

SonarQube Advanced Security

Block risky dependencies early

Gitar AI Code Review image

Gitar AI Code Review

Verify every change before you merge

Sonar Vortex image

Sonar Vortex

Guide and verify coding agents

SonarQube Remediation Agent image

SonarQube Remediation Agent

Clear your backlog and tech debt

SonarQube Hunter Agent image

SonarQube Hunter Agent

The AI security agent that hunts logic flaws

How Sonar can help

The Agent Centric Development Cycle puts the formula to work

Agents get the right context and constraints as they write. Every change receives an independent review across reliability, security, quality, and compliance. Findings get verified fixes before the change ships. Each check produces evidence.

Agentic Loop
CI Verification Loop
Code Maintenance Loop

Fewer iterations, tokens, and build failures

Optimize code generated within the agentic sandbox. Improve agent effectiveness, reduce token costs, improve output quality, and reduce risk.

Proven in the Agentic Loop

36%

Up to 36% lower token consumption

92%

Up to 92% fewer issues in committed code

Sources: Sonar, “Cut your coding agent’s cost with Sonar Vortex,” June 30, 2026; Sonar, “Introducing Sonar Vortex and the SonarQube Remediation Agent,” June 30, 2026

Integrations

Confidence at enterprise scale, with the tools you already use

Plugins for all major coding agents through MCP, CLI, IDE plugins, and hooks.

The proof

Sonar drives better agentic coding outcomes

SonarQube users are more likely to say AI coding has had a very positive impact on…

Code security
81%

more likely

Outage frequency
76%

more likely

Time to market
34%

more likely

Source: Sonar State of Code Developer Survey 2027 (n=1,026; 319 SonarQube users, 707 non-users). Top box only: share saying AI coding had a “very positive” impact. “More likely” is the relative difference vs. non-users.

the latest

News

Intent × Guiderails × Verification × Evidence

On every change. At any volume. At agent speed.

*AI outage risk based on the 2026 Sonar State of Code Developer Survey. Token usage reduction based on Sonar research on agentic coding workflows; results vary by codebase.